In most wireless communication systems, e.g. cellular communication systems, some form of transmit power control is usually necessary in order to use radio resources in an efficient manner while providing a desirable quality of service. For example, in the current UMTS (Universal Mobile Telecommunication System) standard, an uplink transmit power control procedure simultaneously controls a power of a DPCCH (Dedicated Physical Control Channel) and its corresponding DPDCHs (Dedicated Physical Data Channels), if present, a HS-DPCCH (High Speed Dedicated Physical Control Channel), if present, E-DPDCHs (Enhanced Uplink Dedicated Physical Data Channels), if present, and E-DPCCH (Enhanced Dedicated Physical Control Channel), if present. The transmit power control with respect to a UE (User Equipment) comprises an outer-loop power control and an inner-loop power control. While the outer-loop power control adjusts a SIR (Signal-to-Interference-Ratio) target in order to obtain a certain QoS (Quality of Service), the inner-loop power control compares the SIR target with a SIR estimate and generates TPC (Transmit Power Control) commands to inform the UE either to increase or to decrease the transmission signal power.
There are various known methods for performing SIR estimation for the purpose of power control, including in particular: P-over-variance SIR, P-over-beta SIR and GRAKE SIR.
P-over-variance SIR estimate is determined according to
                    SIR        =                                            P              pilots                                      filtered              ⁢                                                          ⁢                              var                ⁡                                  (                  pilots                  )                                                              -                      a            /                                          N                pilot                            .                                                          (        1        )            
Ppilots denotes a received power on pilots. var(pilots) is a variance of the pilots and represents a total interference including white noise, interference from other users and self-interference. The variance var(pilots) is filtered through a smoothing filter before it is used in equation (1). a/Npilot is a so-called bias removal term, where Npilot denotes a number pilots per slot, and where a is a predetermined positive value, which depends on Npilot.
GRAKE (Generalised RAKE (receiver)) SIR estimation is determined according to
                    SIR        =                                                                                                                  w                    H                                    ·                  h                                                            2                                                      w                H                            ·              Ru              ·              w                                .                                    (        3        )            
Here, h is a channel estimate, Ru is an impairment matrix and w is a combing weight. The channel estimate h is here viewed as a complex valued column vector (h ε CM×1), so that
  h  =            (                                                  h              1                                                            ⋮                                                              h              M                                          )        .  
Where M is the number of multi-path components in the channel; M may vary over time. If several antennas are used for receiving the same signal, then each antenna will of course give rise to components in the channel estimate h. In equation (3), the superscript H denotes Hermitian transpose, that is, a conventional matrix transpose combined with complex conjugation of the matrix elements, and the dot denotes matrix multiplication. The channel estimate h may conveniently be thought of as discrete FIR filter modelling an influence of a multi-path radio channel on a transmitted signal. Each component hi of the channel estimate h consequently constitutes a filter tap. The channel estimate h is normally obtained from a received signal by using known information, e.g. pilots, which has been included in the signal when transmitted. Let y be a column vector that represents a received signal corresponding to one transmitted symbol s which is as complex number, then y is related to s by y=hs+n′, where n′ is a complex column vector representing noise, including thermal/background noise, interference form other radio transmitters and self-interference. The impairment matrix Ru ε CM×M is a covariance matrix of the noise vector n′, that is, Ru=E(n′·n′H), where E denotes an expected value. The impairment matrix Ru may be calculated using various approaches. For example, one approach is model based, called parametric GRAKE; another approach is non-model based, called non-parametric GRAKE. Parametric GRAKE estimates Ru mainly based on the channel estimate h and channel delays. Non parametric GRAKE estimates Ru based on the received y and, for instance, unused spreading codes. Once an estimate of the impairment matrix Ru has been obtained, the combining weight w ε CM×1 is calculated based on the impairment matrix and the channel estimate according to w=Ru−1·h. The combining weight w is thereafter used to produce a receiver demodulator output wH·y, often referred to as soft information, which is used for decoding. Above, the notation CI×J is used denote the set of all complex valued I×J matrices for any choice of positive integers I and J. A good introduction to GRAKE techniques can be found, for example, in G. E. Bottomley, T. Ottosson and Y.-P. E. Wang, “A generalized RAKE receiver for interference suppression”, IEEE J. sel Areas Commun., vol. 18, August 2000.
In the P-over-beta SIR method, a real-valued parameter, herein denoted β (beta), which is a measure of an interference power generated by other users and thermal/background noise, is used. Note that β does not take self-interference into account.
Therefore, this approach tries to eliminate inter-symbol interference impact on the SIR estimation. The parameter β can be obtained using different methods. For instance, parametric GRAKE provides a measure of β for each slot using a modelRu=αRsi+βRn, 
where Rsi and Rn are matrices that are obtained based on the channel estimate h and RAKE finger delays. The parameters α and β are estimated from the model using a least square approach.
The parameter β is also filtered with a similar smoothing filter as the filter used in the above-mentioned p-over-variance method. The P-over-beta SIR estimate is determined according to
                    SIR        =                                            P              pilots                                      filtered              ⁢                                                          ⁢                              (                β                )                                              -                      b            /                          N              pilot                                                          (        2        )            
Here b/Npilot is again a bias removal term, where b is a predetermined positive value.
Each SIR estimation method is associated with its own power control behaviour, and the selection of SIR estimation method thus has an important impact on system performance.
Studies have shown that both p-over-variance SIR and p-over-beta SIR have large variance at lower SIR. In general, GRAKE SIR has smallest variance compared with p-over-variance SIR and p-over-beta SIR.
At a higher SIR operating point, multi-path propagation in combination with high transmission power may cause severe self-interference, and in some cases this self-interference may be the dominating source of interference. When self-interference is dominant, a received SIR may not be able to reach the SIR target, irrespective of what transmit power the UE uses. This is due to the fact that increasing the transmission power will also increase the self-interference, and thus the resulting SIR may not be improved as expected. In this case, the inner-loop power control will continue to ask the UE to increase its transmit power, and this will lead to an undesirable power rush, which may lead to system instability, and serious interference also to other system users.
As mentioned above, the p-over-beta SIR method tries to exclude self-interference from the total interference and this method is believed to be able to perform best in cases with dominant self-interference. However, studies have shown that the p-over-beta SIR method cannot completely eliminate self-interference from the total interference. Therefore, occurrences of the above-described power rushes cannot be ruled out altogether.
The GRAKE SIR method is regarded as a good candidate for power control methods, since it has a high accuracy and does not require filtering, which allows the method to follow interference changes quickly. However, self-interference still limits its performance in a context of power control.
Consequently, a problem addressed by the present invention is to overcome or at least mitigate the above-indicated difficulties relating to SIR estimation and power control.